Özet:

Carbon dioxide emission is one of the important factors that have a negative impact on the environment. One of the reasons why policy makers produce incentive policies on renewable energy is that they want to reduce CO2 emissions. From this point of view, prediction of CO2 emissions must be made depending on different factors, and new policies can be developed and implemented according to the prediction results. In this article, a new approach from gray estimation models, NMGM (1, N) forecasting model, is used to measure the impact of renewable energy consumption, non-renewable energy consumption, GDP and Population factors on CO2 emission over time. 2006-2015 data was simulation set and 2016-2019 data was used as a test set. In addition to this method, estimation was made with GM (1, N) and econometric model, which is the multivariate gray estimation method, and the results were compared. As a result, NMGM (1, N) model has become a very effective estimation method with very low deviation values.

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